Overlapping vessels are a fundamentally known problem in digital subtraction angiography (DSA). A large move in the direction of reliable images that can be effectively interpreted was the development of four-dimensional digital subtraction angiography. In four-dimensional digital subtraction angiography, two-dimensional projection images of the recording region of interest of the blood vessel system of the patient are recorded using X-ray equipment (e.g., X-ray equipment having a C-arm, with one or more rotation(s) at different projection angles) while the contrast medium migrates through the blood vessel system in the recording region. Projection images of digital subtraction angiography are produced subtracting a mask image recorded without contrast medium, and a subtraction may also be made for respective reconstructed three-dimensional image data sets. While in the beginnings of digital subtraction angiography it was known to generate a plurality of consecutive three-dimensional image data sets by using projection images from digital subtraction angiography recorded in a particular time interval to reconstruct a three-dimensional partial image data set therefrom, new approaches exist that may provide better image quality and a better temporal resolution.
One of the new approaches is described in an article by B. Davis et al., “4D Digital Subtraction Angiography: Implementation and Demonstration of Feasibility”, DOI: 10.3174/ajnr.A3529. It is proposed to firstly reconstruct a non-time resolved, three-dimensional vessel data set showing the entire blood vessel system in the recording region, using a particularly large portion of the projection images from digital subtraction angiography. The projection images exhibit at least largely filled vessels, and the data set forms the basis for continuously updating of the voxel values by multiplicative embedding of the time information of the (e.g., standardized) projection images from digital subtraction angiography, such that a series of time-resolved 3D images (e.g., of partial image data sets of the four-dimensional angiography data set) is produced. In other words, the vessel data set is ultimately used for limiting the reconstruction of the individual three-dimensional partial image data sets which integrate the time information of the projection images from digital subtraction angiography. A multiplicative back projection is therefore performed. This may be taken to mean that vessels (e.g., voxels marked as vessels) located on the beam of a pixel of a projection image, showing contrast medium filling, are highlighted as being contrast medium-filled at the instant of recording of the projection image.
The use of recordings in a single plane and the multiplicative back projection in the four-dimensional image reconstruction may lead to problems when a vessel overlap exists along the beams of the current projection image. More precisely, the multiplicative back projection of a two-dimensional projection image in a static three-dimensional limitation image (e.g., the vessel data set, without additional regularization) leads to non-plausible vessel highlighting because the contrast information of the two-dimensional projection image may not be unequivocally assigned to one of the overlapping vessels. Therefore, an algorithm of this kind may create artifacts due to vessel overlapping in that particular vessel segments, displayed too early or too late as being filled with contrast medium. For the user (e.g., a doctor making a diagnosis), the image quality and the clinical significance of this four-dimensional are adversely affected.
To reduce the number of overlap artifacts, it has already been proposed, during multiplicative back projection for determining the three-dimensional partial image data sets assigned to different instants, to simultaneously determine a likewise four-dimensional confidence map as a confidence data set describing the vessel overlap along relevant, used beams. The confidence value 0 is conventionally assigned to a strong vessel overlap and a confidence value 1 is conventionally assigned to a non-existent vessel overlap. Confidence values of the confidence data set may be determined by “counting” the vessels (e.g., by integration along the beam and comparison with at least one threshold value). Based on the four-dimensional confidence data set describing the vessel overlap, it is possible to interpolate unreliable intensity values of the provisional four-dimensional angiography image data set between sufficiently reliable neighboring values in the time and therefore replace the less reliable values (e.g., those falling below a threshold value for the confidence value).
However, it has been found that more potential for improvement exists for this approach with the elimination of the image quality problem due to vessel overlap artifacts.